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Search Results: 1 - 10 of 127048 matches for " Kezhi Li "
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A Brief Survey of Image Processing Algorithms in Electrical Capacitance Tomography
Kezhi Li
Computer Science , 2015,
Abstract: To study the fundamental physics of complex multiphase flow systems using advanced measurement techniques, especially the electrical capacitance tomography (ECT) approach, this article carries out an initial literature review of the ECT method from a point of view of signal processing and algorithm design. After introducing the physical laws governing the ECT system, we will focus on various reconstruction techniques that are capable to recover the image of the internal characteristics of a specified region based on the measuring capacitances of multi-electrode sensors surrounding the region. Each technique has its own advantages and limitations, and many algorithms have been examined by simulations or experiments. Future researches in 3D reconstruction and other potential improvements of the system are discussed in the end.
Distribution of displacement in backward spinning of tube
Kezhi Li,Yan Lü
Chinese Science Bulletin , 1997, DOI: 10.1007/BF02882559
State of the Art and Prospects of Structured Sensing Matrices in Compressed Sensing
Kezhi Li,Shuang Cong
Mathematics , 2014, DOI: 10.1007/s11704-015-3326-8
Abstract: Compressed sensing (CS) enables people to acquire the compressed measurements directly and recover sparse or compressible signals faithfully even when the sampling rate is much lower than the Nyquist rate. However, the pure random sensing matrices usually require huge memory for storage and high computational cost for signal reconstruction. Many structured sensing matrices have been proposed recently to simplify the sensing scheme and the hardware implementation in practice. Based on the restricted isometry property and coherence, couples of existing structured sensing matrices are reviewed in this paper, which have special structures, high recovery performance, and many advantages such as the simple construction, fast calculation and easy hardware implementation. The number of measurements and the universality of different structure matrices are compared.
A Robust Compressive Quantum State Tomography Algorithm Using ADMM
Kezhi Li,Shuang Cong
Computer Science , 2014,
Abstract: The possible state space dimension increases exponentially with respect to the number of qubits. This feature makes the quantum state tomography expensive and impractical for identifying the state of merely several qubits. The recent developed approach, compressed sensing, gives us an alternative to estimate the quantum state with fewer measurements. It is proved that the estimation then can be converted to a convex optimization problem with quantum mechanics constraints. In this paper we present an alternating augmented Lagrangian method for quantum convex optimization problem aiming for recovering pure or near pure quantum states corrupted by sparse noise given observables and the expectation values of the measurements. The proposed algorithm is much faster, robust to outlier noises (even very large for some entries) and can solve the reconstruction problem distributively. The simulations verify the superiority of the proposed algorithm and compare it to the conventional least square and compressive quantum tomography using Dantzig method.
Distribution of displacement in backward spinning of tube

Kezhi Li,Yan Lü,

科学通报(英文版) , 1997,
CVD Treatment of Carbon Fibers and Evaluation of Their Dispersion in CFRC  [PDF]
Chuang Wang, Bingliang Li, Lei Peng, Wenmin He, Liping Zhao, Kezhi Li
Materials Sciences and Applications (MSA) , 2017, DOI: 10.4236/msa.2017.88046
Abstract: Carbon-fiber-reinforced cement-based (CFRC) composites is a promising functional material which can be used both in the military and civil fields against electromagnetic interference. However, it is essential to make carbon fibers dispersed uniformly during the preparation of CFRC. In this work, short carbon fibers were treated through Chemical Vapor Deposition (CVD) process at high temperature between 900°C and 1200°C under the protection of diluted nitrogen gas N2 to modify the surface of carbon fibers to further strengthen the bonding between carbon fibers and cement matrix. Natural gas (98% CH4) was used as a precursor. It was decomposed to produce an uneven layer of pyrocarbon that was deposited on the surface of carbon fibers. CVD-treated carbon fibers were pre-dispersed by using ultrasonic wave. Both hydroxyethyl cellulose (HEC) and silicon fume were used as dispersants and as admixtures. They helped CVD-treated carbon fibers distribute uniformly. The mass fraction of HEC was around 1.78% in the aqueous solution. Four methods, namely, the simulation experiment (SE) method, the scanning electron microscopy (SEM) method, the fresh mixture (FM) method, and the electrical resistivity measurement (ERM) method were, respectively, applied to evaluate fiber dispersion degree. Each method indicated its own advantages and disadvantages and it therefore catered for different conditions. Of the four evaluation methods, the SE method was the most convenient way to determine the pre-dispersion state prior to the preparation of CFRC composites. This method was helpful for predicting the subsequent dispersion state of carbon fibers in the cement matrix because it economized a large quantity of raw materials and time.
Orthogonal symmetric Toeplitz matrices for compressed sensing: Statistical isometry property
Kezhi Li,Lu Gan,Cong Ling
Mathematics , 2010,
Abstract: Recently, the statistical restricted isometry property (RIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this paper, we propose the usage of orthogonal symmetric Toeplitz matrices (OSTM) for compressed sensing and study their statistical RIP by taking advantage of Stein's method. In particular, we derive the statistical RIP performance bound in terms of the largest value of the sampling matrix and the sparsity level of the input signal. Based on such connections, we show that OSTM can satisfy the statistical RIP for an overwhelming majority of signals with given sparsity level, if a Golay sequence used to generate the OSTM. Such sensing matrices are deterministic, Toeplitz, and efficient to implement. Simulation results show that OSTM can offer reconstruction performance similar to that of random matrices.
Convolutional Compressed Sensing Using Deterministic Sequences
Kezhi Li,Lu Gan,Cong Ling
Computer Science , 2012, DOI: 10.1109/TSP.2012.2229994
Abstract: In this paper, a new class of circulant matrices built from deterministic sequences is proposed for convolution-based compressed sensing (CS). In contrast to random convolution, the coefficients of the underlying filter are given by the discrete Fourier transform of a deterministic sequence with good autocorrelation. Both uniform recovery and non-uniform recovery of sparse signals are investigated, based on the coherence parameter of the proposed sensing matrices. Many examples of the sequences are investigated, particularly the Frank-Zadoff-Chu (FZC) sequence, the \textit{m}-sequence and the Golay sequence. A salient feature of the proposed sensing matrices is that they can not only handle sparse signals in the time domain, but also those in the frequency and/or or discrete-cosine transform (DCT) domain.

FU Qiangang,LI Hejun,LI Kezhi,SHI Xiaohong,

金属学报 , 2009,
Influences of double aerial CO2 concentration on plant root surface area and viability and infection intensity of vesicular-arbuscular mycorrhizal fungi
Xingfen Wang,Shiyi Li,Kezhi Bai,Tingyun Kuang
Chinese Science Bulletin , 1999, DOI: 10.1007/BF03182887
Abstract: Using recently developed methods for root research, an investigation initiated concerning effects of doubled atmospheric CO2 concentration on root surface area and infection of vesicular-arbuscular mycorrhizal (VAM) fungi in seedlings of maize, wheat and soybean. Results showed that doubled CO2 concentration significantly extended root system surface area and promoted VAM fungal infection intensity and viability. However, interspecific variation existed in these responses. It is suggested that plant community succession would be changed due to altered characteristics of roots among species in the future climate.
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